[GiNaC-list] Using polynomial power series for solving PDEs

[Foad Sojoodi Farimani]

Hello guys again,

I'm not sure if you have received my former email but I'm gonna reply to
that so you can read it as well:

While ago I was trying to use polynomial power series to solve a system of
partial differential and algebraic equations, when realized there is no
implementation of the idea. There is only Mathematica's
AsymptoticDSolveValue which is just for ODEs. So I decided to implement it
myself. Thanks to the Sympy community we now have some progress. I have one
implementation over here
<http://nbviewer.jupyter.org/gist/celliern/b38158d04d9dc3d8079dc44e3b747ac8>
 by Nicolas CELLIER <https://github.com/celliern> and some ideas over here
<https://cs.stackexchange.com/questions/95886/algorithm-for-using-power-series-to-numerically-solve-a-partial-differential-equ>
 by me and some of SymPy developers. I was wondering if we could join
forces to come of with a general algorithm, then implementionation on
diffrent languages shouldn't be that difficult. I was wondering if you
could take a look at this question
<https://cs.stackexchange.com/questions/95886/algorithm-for-using-power-series-to-numerically-solve-a-partial-differential-equ>
 and help us out.

FYI I have made a issue on SymPy's github over here
<https://github.com/sympy/sympy/issues/15015#> which you can follow.

Best,
Foad


On Thu, Aug 2, 2018 at 9:40 AM Foad Sojoodi Farimani <f.s.farimani at gmail.com>
wrote:

> Hello everyone,
>
> I want to generate a multivariate polynomial given an array of nonnegative
> integers D=[d1,...,dm].  I want to replicate what I have been suggested
> in SymPy, in GiNaC, to see if I can get a better performance. (see here
> <https://groups.google.com/forum/#!topic/sympy/V4KRzA-3doI>, here
> <https://gist.github.com/Foadsf/07d4649f94f4d71876612a0ec6d9939b>and here
> <https://stackoverflow.com/questions/51628270/how-to-generate-a-symbolic-multivariate-polynomial-of-a-given-dimension-in-sympy>)
> I would appreciate if you could help me with this.
>
> Best,
> Foad
>
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